The invented method is a process to evaluate drug effect in a multiple dose clinical trial, similar to sample inspection of a product in manufacturing. In drug development, drug developers are required by federal laws to find an optimal dose and to demonstrate that the selected dose is safe and efficacious. Normally, a relatively small scaled phase II clinical trial is carried out to find a proper dose. Then an adequate and well-controlled phase III clinical trial will be conducted to confirm the results from the phase II clinical trial. In many practical situations, the number of patients in each dose group at the phase II trial can not be as large as it should be. This is because the total number of patients is the number of patients per group multiplied by the number of dose groups in the trial. A moderate increase in the number of patients in each dose group will be a substantial increase of total number of patients in the clinical trial. Drug developers can not afford both a large dose-finding clinical trial and then a large confirmatory clinical trial. If a dose-finding trial does not have an appropriate sample size, the selected dose might not be the optimal for the treatment. On the other hand, if both large phase II and phase III trials are carried out, clinical trials could be very costly and lengthy. Some useful information of drug effect in the phase II trial is wasted. Therefore, it is desired to perform a necessarily large dose-finding trial and use the data from this trial as a part of to-be-conducted phase III clinical trial for final evaluation. However, there are concerns to pool the data from dose-finding trial with the data from confirmatory trial. What has been concerned most is that the true drug effect of the selected dose might be overestimated by the highest observed response rate if a dose is determined by which dose group has the highest observed response rate. Currently, the most popular method for this problem is Bonfferroni Adjustment. But Bonfferroni Adjustment overacts when it corrects the overestimation, therefore, is known to be too conservative. The invented method improves Bonfferroni Adjustment and fills the gap between overestimating and being too conservative. As a result, clinical trials are less expensive to conduct and faster to complete. Results of the said method can also be used as evidence in the New Drug Application to be presented to the Food and Drug Administration (FDA) to seek claims for the test drug. Finally, results of the said method and the claims of the drug being supported can be used both in the labeling of the drug to educate the professionals and costumes and in advertisement to promote market shares of the drug when it completes with other drugs.
Overestimation means that an estimate is frequently greater than true value being estimated. We can use response rate as an indicator of successfulness of a dose. When we choose a dose with the highest observed response rate among dose groups, this observed response rate could overestimate true response rate of the selected dose. For example, if true response rates of dose A and dose B are the same, say 75%, then the higher of the observed rates in the two dose groups will be very likely greater than 75% due to sample variation. Then we might tend to believe that the selected dose has a response rate greater than 75%. On the other hand, this problem may not be as serious as what we have just illustrated when true response rates of competing doses are significantly different. If true response rates of dose A and dose B are 85% and 55%, respectively, dose A will almost certainly be chosen by the higher response rate in observation and the overestimation of response rate of the selected dose is unlikely a problem. But we do not know the true response rate of each dose group and the observed response rates may vary due to sample variation. This invention is a sophisticated method that decides when and how to make a correction. In practice, the FDA repeatedly requests drug developers to use Bonfferroni Adjustment to make corrections no matter what.
The paper of Sankoh, Huque and Dubey [1] is one of the best that described the problem and reviewed the existing methods. D'Agostino, Massaro, Hwan and Cabral [2] also discussed the methods to deal with multiple dose comparisons in confirmatory trials. Among various approaches, Bonfferroni's procedure is the most accepted approach because of its conservative nature. Other methods are rarely used by drug developers and thus, are not worth mentioning here. Bonfferroni's procedure raises confidence level of each comparison between a dose group and the competing drug so that the overall confidence level of comparison between the test drug and the competing drug is guaranteed. As a result, it overacts in correcting potential overestimation. Furthermore, it provides no estimate of true response rate but a significant level of statistical tests in comparison with a control group. Therefore, Bonfferroni Adjustment is not a satisfactory approach for the pharmaceutical industry in seeking a method that will appropriately correct overestimation when it is necessary.